Skripsi

OPTIMASI DERAJAT KEANGGOTAAN FUZZY TSUKAMOTO MENGGUNAKAN GENETIC ALGORITHM UNTUK MENENTUKAN KECUKUPAN GIZI PADA POLA MAKANAN BALITA

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Penilaian

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This study discusses the use of genetic algorithms to optimize the degree of membership in Fuzzy Tsukamoto in the case of determining the nutritional adequacy of the toddler's diet. Use of Fuzzy Tsukamoto will tolerate malnutrition so that the value is not decisive, while the use of genetic algorithms will optimize fuzzy membership degree range so that the resulting solution will be optimized. The performance of the Fuzzy Tsukamoto method whose membership degree is optimized by the genetic algorithm is by using the parameters mr = 0.3, cr = 0.7, population = 100, and iteration = 50. From the test it was found that the use of genetic algorithms reached 53.33% as the highest accuracy and 49.33% as the average accuracy. While the accuracy of the degree of membership without optimization is obtained by 40%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002699	T52637	T526372021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T526372021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xvi, 108 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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